Arbeitspapier
Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables
In this paper, the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables are investigated. Some sufficient conditions for the convergence are provided. In addition, the Marcinkiewicz-Zygmund type strong law of large numbers for weighted sums of extended negatively dependent random variables is obtained. The results obtained in the article extend the corresponding ones for independent random variables and some dependent random variables.
- Language
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Englisch
- Bibliographic citation
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Series: IRTG 1792 Discussion Paper ; No. 2018-040
- Classification
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Wirtschaft
Mathematical and Quantitative Methods: General
- Subject
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Extended negatively dependent
complete convergence
complete moment convergence
maximal weighted sums
strong law of large numbers
- Event
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Geistige Schöpfung
- (who)
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Yan, Ji Gao
- Event
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Veröffentlichung
- (who)
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Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
- (where)
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Berlin
- (when)
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2018
- Handle
- Last update
-
10.03.2025, 11:43 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Yan, Ji Gao
- Humboldt-Universität zu Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"
Time of origin
- 2018
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